To get us started, I have provided some summary statistics and data visualizations with the WERN data. I have divided this analysis into three sections. The first provides a snapshot of the warehouse workforce, the second details responses to our warehouse-specific questions, and the third compares warehouse workers to workers in other industries.

There are a few things to keep in mind:

  • I have not included all variables but only ones that seemed most pertinent
  • Some variables that were not included or that don’t appear intriguing at first blush may become interesting in multivariate analyses
  • I have generally dropped respondents who put down “Don’t know”–I am no sure if this is an appropriate choice

Next steps:

  • Determine which bi - or multi-variate analysis to conduct
  • Consider some sort of factor analysis

Worker profile

In this section, we get a glimpse of who works inside warehouses.

Demographics

Gender

Race

Age

Geographic distribution

The following shows where survey respondents are located.

Employment characteristics

Employment type

Number of jobs held

Tenure

Union representation

Voice

Warehouse-specific items

In this section, we see how workers responded to questions designated for the warehouse industry.

Warehouse characteristics

Type of warehouse

Warehouse technology

Company characteristics

Promotion opportunities

Job mobility

Replacement by temps

Replacement by technology

Worker retention

Safety

Supervisor support

Job characteristics

Pace of work

Autonomy

Pace monitoring

Monitoring intensity

Productivity comparisons

Performance postings

Production anxiety

Bathroom break

Meeting standards

Industry comparisons

In this section, we see how warehouse workers compare to workers in other industries.

Employment prospects

Job security

Ease of finding new job

Likelihood of seeking new job

Job characteristics

Working alone

Team stability

Surveillance

Scheduling

More hours

Advance notice

Time off ease

Schedule control

Time off control

Black out periods

Supervisor schedule accomodation

Shift/timing changes

Canceled shifts

Work-life stress

Caregiving conflict

Personal issues conflict

Work relations

Manager retaliation

Union vote